Product Review Classification

This tool uses sentiment analysis to classify product reviews as negative or positive.

We use Nestle Official Store and Unilever Official Store from Tokopedia Marketplace as our dataset to train this model. So there may be limitations on the reviews that can be used in this application.

LIVE DEMO: Product Review Classification

You can try this app from the link above.

Important

Before going into this main section, you need to check the other important sections

• Review Scraping Tools : How we created our dataset from Nestle & Unilever product reviews
• Notebooks & Dataset : How we processed dataset & build model to make review classification
• React Web Front-End : How we built front-end with React to try our model in one click
• Server Back-End : How we built back-end with Flask to provide API to handle request from front-end

You must follow the above instructions before running this application

Prerequisites

You are required to install Python 2.7 and pip Package Installer to run this app.

1. Download and Install Python 2.7 at https://www.python.org/download/releases/2.7
2. Follow instructions to Install pip at https://pip.pypa.io/en/stable

Installation

Install required modules to use this tools.

python -m pip install -r requirements.txt

Usage

python wsgi.py

You can access the app through http://localhost:5000

Check the tutorial how to edit and build the front-end here.

Deploy

If you want to deploy this app to heroku, you need follow the instructions at https://devcenter.heroku.com/articles/git

DEPLOYED DEMO: Product Review Classification at Heroku